id stringlengths 11 11 | created timestamp[s]date 2026-01-01 00:00:00 2026-01-01 00:00:00 | topic stringclasses 14 values | task_type stringclasses 10 values | difficulty stringclasses 3 values | instruction stringlengths 189 248 | input stringclasses 1 value | output stringclasses 9 values | reasoning_steps listlengths 0 5 | metadata dict | hash stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|
train_02100 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | data_pipeline | advanced | Task: data_pipeline
Topic: Tool calling, sandboxes, and CI integration
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"tooling",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bedb944450130fbe707716004079938b223ffe21 | |
train_02101 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | compare | advanced | Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"tests_are_truth",
"documentation"
],
"moe_experts": [
"agentic_systems_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b3c463fc5c5697e47b5617ff548d124be8fb5497 | |
train_02102 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | agent_loop | intermediate | Task: agent_loop
Topic: Tool calling, sandboxes, and CI integration
Difficulty: intermediate
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"tooling",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d3c55836b5e7d8ad6c524a7350b534d6caf67df4 | |
train_02103 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | intermediate | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"documentation",
"security_gates",
"auditability",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 390f5a0099e4cc6e72c9fbe45b265db29f8f6132 | |
train_02104 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | patch_diff | intermediate | Task: patch_diff
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"auditability",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 205b10828e58b0c7b28dca5397e808f39b13149e | |
train_02105 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | patch_diff | advanced | Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"tooling",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5ea155024e26b1c85c7b4e35bd7459575c2735b7 | |
train_02106 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | expert | Task: eval
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Bash
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"documentation",
"reproducibility",
"evaluation_metrics",
"governance"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 77db71fddf5bde859f7b4bc4a14e3ead264b07e0 | |
train_02107 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | eval | advanced | Task: eval
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"tests_are_truth",
"documentation",
"security_gates",
"tooling"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3c26b05da744f550842b88169082eb993b8cb43e | |
train_02108 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | expert | Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"auditability",
"documentation",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | be62511b2fe1b17704834cfd463e96c5e536fd8b | |
train_02109 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | patch_diff | expert | Task: patch_diff
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"tests_are_truth",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e9cd261aa831ac7a14c4758c00287031e728508d | |
train_02110 | 2026-01-01T00:00:00 | Secure code generation and policy gates | eval | intermediate | Task: eval
Topic: Secure code generation and policy gates
Difficulty: intermediate
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"reproducibility",
"security_gates",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c3f5c181b4b75c871136d2c8127c6c0f6de348a9 | |
train_02111 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | eval | advanced | Task: eval
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Java",
"developer_needs": [
"reproducibility",
"tooling",
"repo_scale_reasoning",
"tests_are_truth"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f85f43a4bd67f27195adb2dda8b7798977fb7d7b | |
train_02112 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | patch_diff | expert | Task: patch_diff
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"tooling",
"security_gates",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 408942538dc6fa7f8c54adc5e777c5b9348983e2 | |
train_02113 | 2026-01-01T00:00:00 | Secure code generation and policy gates | explain | expert | Task: explain
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"repo_scale_reasoning",
"auditability",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7179fce5abfbcd19d14f300ed94aa37c2807a45b | |
train_02114 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | explain | expert | Task: explain
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"governance",
"tooling",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 74d2477c207feaea0d5c6d2d647fe661fbef3261 | |
train_02115 | 2026-01-01T00:00:00 | Tool calling, sandboxes, and CI integration | code | expert | Task: code
Topic: Tool calling, sandboxes, and CI integration
Difficulty: expert
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"security_gates",
"tooling"
],
"moe_experts": [
"governance_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ddbd629fa57a6374018fabb8a98e0010b519933e | |
train_02116 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | agent_loop | advanced | Task: agent_loop
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Rust
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6f16beec1f142c9bef1f27c1503cc6658e869bc9 | |
train_02117 | 2026-01-01T00:00:00 | Secure code generation and policy gates | review | advanced | Task: review
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"documentation",
"cost_latency_tradeoffs",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 19eb337c6f85eeb93641e21e5c656f477c70af36 | |
train_02118 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | advanced | Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"security_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dafa5220d70659302be128e5f098d6ea385cdb8f | |
train_02119 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | failure_analysis | advanced | Task: failure_analysis
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: advanced
Target language: SQL
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"security_gates",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9074539fa9a0aee5978d8bca9b55362e4841c3aa | |
train_02120 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | advanced | Task: code
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"tooling",
"auditability",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 7804df1da499a7194d8abc14c6534e13452e4415 | |
train_02121 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | patch_diff | advanced | Task: patch_diff
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"documentation",
"tests_are_truth",
"security_gates",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a8ffd31a63f06aa014ce2fb7bd91479fc8bff376 | |
train_02122 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | review | advanced | Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"security_gates",
"governance",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3d9ebeac1cbaea7e9d85ca4267df6b7674bcd6c8 | |
train_02123 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | explain | advanced | Task: explain
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"security_gates",
"auditability"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a86da61187b5c0caab8701754a357ca827a782cc | |
train_02124 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: Python
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dd2bf051c9b9d99c9413d17ef1e393ceb4be08b4 | |
train_02125 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | expert | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"governance",
"ci_integration"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8982f5c1093ead68741db1c1b01c22c8d1c22d42 | |
train_02126 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | compare | expert | Task: compare
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "SQL",
"developer_needs": [
"documentation",
"governance",
"tooling",
"security_gates"
],
"moe_experts": [
"governance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9b56a2a40b1a80a88e2442734354abb2b18416de | |
train_02127 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | expert | Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"security_gates",
"ci_integration",
"reproducibility"
],
"moe_experts": [
"security_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2c0cb02d2979ef213dd4ad360239e4eb79801b74 | |
train_02128 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | advanced | Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: advanced
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Rust",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"evaluation_metrics",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 008c75d926378ea9c5772fe6b62dd613b3b39c06 | |
train_02129 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | explain | advanced | Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"documentation",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 757ecdba8f9cc36ccb557148705ce97d1c114d88 | |
train_02130 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | expert | Task: design
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: Python
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"documentation",
"security_gates",
"tooling"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4432df4713420fbe525b1f0d5a89d7f2837bf63f | |
train_02131 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | explain | intermediate | Task: explain
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Java",
"developer_needs": [
"repo_scale_reasoning",
"evaluation_metrics",
"security_gates",
"cost_latency_tradeoffs"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 92fee0ba901177d655039a5c70c6fc9c024a5937 | |
train_02132 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | expert | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: expert
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"ci_integration",
"evaluation_metrics"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 87fa38c5d8fadaac930e75868e8bdb9edbb5ef24 | |
train_02133 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | review | advanced | Task: review
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: Rust
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"repo_scale_reasoning",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"data_curation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a0356e221a14dbbeb3fe30c1b95d4d55484f8d17 | |
train_02134 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | explain | advanced | Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"tests_are_truth",
"governance",
"cost_latency_tradeoffs",
"auditability"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 87a5263c3f1344c6a407aabe57d92c15c43a8f03 | |
train_02135 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | advanced | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"reproducibility",
"repo_scale_reasoning",
"tooling",
"auditability"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c90cc3a29a8897a7e3e4e305a3657ea1fd4577c8 | |
train_02136 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | agent_loop | expert | Task: agent_loop
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "SQL",
"developer_needs": [
"repo_scale_reasoning",
"governance",
"documentation",
"tooling"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 42cd0531e9e8eff3e3d6210d1c7b1d1e6c50c304 | |
train_02137 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | eval | advanced | Task: eval
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "C#",
"developer_needs": [
"reproducibility",
"evaluation_metrics",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f6b31fe3b036c950416aa4eda49e1f5ccfdf2f51 | |
train_02138 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | expert | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Python",
"developer_needs": [
"ci_integration",
"evaluation_metrics",
"reproducibility",
"documentation"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9c9505a3facd3120bf4890c017fb6c9de2a23c4a | |
train_02139 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | design | intermediate | Task: design
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"auditability",
"documentation",
"tooling",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ccb2f7370c5bbe8cbd1917cdc5aa5a3c75fbe4da | |
train_02140 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | compare | expert | Task: compare
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"tests_are_truth",
"cost_latency_tradeoffs",
"tooling",
"auditability"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a736c28a4a1c15bcaf15a28476793ce7c449cf2f | |
train_02141 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | data_pipeline | intermediate | Task: data_pipeline
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"governance",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 9dbb2f615670948f1d63eb5b6990a54ec34dd79f | |
train_02142 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | review | advanced | Task: review
Topic: Extended context and repo-scale understanding
Difficulty: advanced
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"tooling",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a14b2e14df60db8c6439f21ed5603e05a8fe7b38 | |
train_02143 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | code | expert | Task: code
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3775a586e1096557ae8e709af7e5f197ead18d17 | |
train_02144 | 2026-01-01T00:00:00 | Secure code generation and policy gates | compare | expert | Task: compare
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"evaluation_metrics",
"reproducibility",
"auditability"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 473ddc210ecad46b6e778f25db852b61227ca347 | |
train_02145 | 2026-01-01T00:00:00 | Secure code generation and policy gates | data_pipeline | expert | Task: data_pipeline
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"evaluation_metrics",
"tooling",
"documentation",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 635aeffc6f52fdb48fdb948b5ed9af400f572e17 | |
train_02146 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | agent_loop | expert | Task: agent_loop
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"tooling",
"governance",
"tests_are_truth",
"reproducibility"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | db9bf85c3182bf2e31c13c62def526feea5517a5 | |
train_02147 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | intermediate | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: intermediate
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"ci_integration",
"documentation"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 319825c48b7c2c6ee27d6ffb7e08f3f6428bb5e2 | |
train_02148 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | agent_loop | intermediate | Task: agent_loop
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: intermediate
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "C#",
"developer_needs": [
"repo_scale_reasoning",
"tooling",
"tests_are_truth",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | bee3f650345c67566576331d2e2070fc27cc07e9 | |
train_02149 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | review | advanced | Task: review
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"tests_are_truth",
"governance",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d147ba0dc641a333abc92a3f07c512ae1ec08b7f | |
train_02150 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | review | intermediate | Task: review
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"evaluation_metrics",
"ci_integration",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | de098c8e920ab02650e73c0ebcacddaf0c285b22 | |
train_02151 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | agent_loop | expert | Task: agent_loop
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: SQL
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "SQL",
"developer_needs": [
"tests_are_truth",
"governance",
"cost_latency_tradeoffs",
"reproducibility"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | a19f27e125522fad1fbbc9a648aa169c11da0a44 | |
train_02152 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | design | intermediate | Task: design
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"reproducibility",
"cost_latency_tradeoffs",
"tooling",
"ci_integration"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 90ef92d0f50336c1d1624b0fb09dddf73cef6452 | |
train_02153 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | agent_loop | intermediate | Task: agent_loop
Topic: Extended context and repo-scale understanding
Difficulty: intermediate
Target language: Java
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"security_gates",
"ci_integration",
"repo_scale_reasoning"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cb9c50c8b0befef8b26d6c56b6fb7c17c09348db | |
train_02154 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | review | expert | Task: review
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"repo_scale_reasoning",
"auditability",
"reproducibility",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 12f14dbb7c5d5646e20e6c2e98095fe19c287ef3 | |
train_02155 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | patch_diff | intermediate | Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: C#
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "C#",
"developer_needs": [
"governance",
"cost_latency_tradeoffs",
"reproducibility",
"evaluation_metrics"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 94746e4ea50c0b4caa0549466712d1c3094aae7b | |
train_02156 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | intermediate | Task: code
Topic: Model merging, distillation, and continued pretraining
Difficulty: intermediate
Target language: Go
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"governance",
"security_gates",
"repo_scale_reasoning",
"cost_latency_tradeoffs"
],
"moe_experts": [
"performance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 058ce2778aa6b939e0a9e80f94b0493d51b51a05 | |
train_02157 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | review | intermediate | Task: review
Topic: SWE-bench style real-repo evaluation
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"evaluation_metrics",
"governance",
"documentation",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0ed7fadb6e2ef2e72b00db96ff46729ac9c6cf3a | |
train_02158 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | failure_analysis | expert | Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Bash
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "Bash",
"developer_needs": [
"auditability",
"ci_integration",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | d557e21fe235028d0e707cdf3ae8c17e1bc7feb5 | |
train_02159 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | intermediate | Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: intermediate
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"ci_integration",
"auditability",
"tests_are_truth"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 078ac111116620df8be2942f8ccaf7eecde43577 | |
train_02160 | 2026-01-01T00:00:00 | Secure code generation and policy gates | failure_analysis | expert | Task: failure_analysis
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"reproducibility",
"governance",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 51a11675b4682715d495495f667c06d81c945e1c | |
train_02161 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | expert | Task: code
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"security_gates",
"tests_are_truth",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | cc788e17d198436d5092f57410bfb0f44760d279 | |
train_02162 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | code | advanced | Task: code
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: advanced
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"reproducibility",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f005291ca05201ecb9be66e2d4eba8ed58d6ac8a | |
train_02163 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | patch_diff | expert | Task: patch_diff
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: expert
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Rust",
"developer_needs": [
"auditability",
"ci_integration",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 256c5e34dddcc07f3176ed1acb32f8bd61a667c5 | |
train_02164 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | eval | intermediate | Task: eval
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: intermediate
Target language: Rust
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Rust",
"developer_needs": [
"ci_integration",
"repo_scale_reasoning",
"tooling",
"auditability"
],
"moe_experts": [
"security_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 2a8eb02b74cc419003d73c5e172e67be10de9c38 | |
train_02165 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | data_pipeline | expert | Task: data_pipeline
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Bash
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "Bash",
"developer_needs": [
"governance",
"repo_scale_reasoning",
"documentation",
"reproducibility"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f20020deeff1692a2bb2d69c225a90e22b583743 | |
train_02166 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | code | expert | Task: code
Topic: Latency, cost, and reliability optimization
Difficulty: expert
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"cost_latency_tradeoffs",
"ci_integration",
"evaluation_metrics",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 41495c9711b3ae16ffbab71fd8573df437e1822c | |
train_02167 | 2026-01-01T00:00:00 | Secure code generation and policy gates | design | advanced | Task: design
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Go
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Go",
"developer_needs": [
"tooling",
"governance",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4f3628b4bc4a9634bfc7f92c88fa8b482b2105f1 | |
train_02168 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | explain | expert | Task: explain
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: expert
Target language: C#
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"evaluation_metrics",
"governance",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6bc9ed12ff71c364809defe21a623a16abef67c9 | |
train_02169 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | eval | advanced | Task: eval
Topic: Latency, cost, and reliability optimization
Difficulty: advanced
Target language: Bash
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "Bash",
"developer_needs": [
"repo_scale_reasoning",
"reproducibility",
"security_gates",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 25d41920df1c4806bf8e5b34d21157dbda013b20 | |
train_02170 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | data_pipeline | advanced | Task: data_pipeline
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [] | {
"target_language": "SQL",
"developer_needs": [
"reproducibility",
"ci_integration",
"evaluation_metrics",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 4d9c6370c52a9dc1ecdccf393da7dfd7abe9d5f6 | |
train_02171 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | design | expert | Task: design
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Rust
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Rust",
"developer_needs": [
"reproducibility",
"governance",
"documentation",
"auditability"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 6b877419056b01ced904c8749934d65be9432696 | |
train_02172 | 2026-01-01T00:00:00 | Secure code generation and policy gates | design | advanced | Task: design
Topic: Secure code generation and policy gates
Difficulty: advanced
Target language: Python
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"auditability",
"cost_latency_tradeoffs",
"tooling",
"ci_integration"
],
"moe_experts": [
"performance_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8473986b891b667207d7a1df99dbe0daac5c5ec8 | |
train_02173 | 2026-01-01T00:00:00 | Agentic coding systems (plan→edit→test→reflect) | agent_loop | advanced | Task: agent_loop
Topic: Agentic coding systems (plan→edit→test→reflect)
Difficulty: advanced
Target language: TypeScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"evaluation_metrics",
"tests_are_truth"
],
"moe_experts": [
"performance_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f8a47e82babe59f13035a119e38591fda61171dd | |
train_02174 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | compare | advanced | Task: compare
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: advanced
Target language: TypeScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"auditability",
"governance",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0e84472e12e36586d5ba1045140fac4311aaf084 | |
train_02175 | 2026-01-01T00:00:00 | Code-specialized model families and sizing tradeoffs | agent_loop | intermediate | Task: agent_loop
Topic: Code-specialized model families and sizing tradeoffs
Difficulty: intermediate
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"evaluation_metrics",
"governance",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 593ad7b4356d14c5e073294b34b0210dba583488 | |
train_02176 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | eval | expert | Task: eval
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: C#
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"evaluation_metrics",
"reproducibility",
"cost_latency_tradeoffs",
"tests_are_truth"
],
"moe_experts": [
"evaluation_expert",
"agentic_systems_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f86f21ff3c4dadcce1e18c09f7e11d7329474f92 | |
train_02177 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | patch_diff | expert | Task: patch_diff
Topic: SWE-bench style real-repo evaluation
Difficulty: expert
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"auditability",
"evaluation_metrics"
],
"moe_experts": [
"security_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 488a0b3281011bf8533f7ac504b32219d2da5bd4 | |
train_02178 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | failure_analysis | expert | Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: C#
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "C#",
"developer_needs": [
"cost_latency_tradeoffs",
"security_gates",
"repo_scale_reasoning",
"governance"
],
"moe_experts": [
"data_curation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dc042cd7ddcb9f4d528973ce8cec0ae9f316e80e | |
train_02179 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | data_pipeline | advanced | Task: data_pipeline
Topic: Mixture-of-Experts (MoE) for code
Difficulty: advanced
Target language: Go
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Pipeline:
Ingest → Normalize → Filter → Dedupe → Quality → Mix → Audit
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"auditability",
"repo_scale_reasoning",
"reproducibility",
"documentation"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 788b7e2ce80014ea8c7816fd4b563a6399d01004 | |
train_02180 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | eval | expert | Task: eval
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: JavaScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Eval:
pass@k, time-to-green, regressions, diff size
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"auditability",
"tooling",
"evaluation_metrics",
"documentation"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | eb781d69c15aa4a33a903a45df7c8214ea2efb15 | |
train_02181 | 2026-01-01T00:00:00 | Reasoning-first coding models and tunable deliberation | design | intermediate | Task: design
Topic: Reasoning-first coding models and tunable deliberation
Difficulty: intermediate
Target language: Java
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"cost_latency_tradeoffs",
"governance"
],
"moe_experts": [
"security_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 86af4a5a31302810dabbf1502551bc18391c7b9e | |
train_02182 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | patch_diff | expert | Task: patch_diff
Topic: Self-improving agents and feedback loops
Difficulty: expert
Target language: Java
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "Java",
"developer_needs": [
"evaluation_metrics",
"cost_latency_tradeoffs",
"ci_integration",
"documentation"
],
"moe_experts": [
"performance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dee8dd69b18ef45a1020b5de1902051aabd5be5c | |
train_02183 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | patch_diff | expert | Task: patch_diff
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: SQL
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Patch (diff-style):
```diff
- if x == 0:
- return 1/x
+ if x == 0:
+ raise ValueError('division by zero')
```
Acceptance:
- Tests pass
- No new regressions
| [] | {
"target_language": "SQL",
"developer_needs": [
"security_gates",
"cost_latency_tradeoffs",
"ci_integration",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | f2b185780732c289f517cb3553fbe11f7aa7f5ca | |
train_02184 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | code | expert | Task: code
Topic: Model merging, distillation, and continued pretraining
Difficulty: expert
Target language: Python
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Scaffold:
```python
def agent_loop(plan, edit, test, issue, max_iters=4):
history = []
p = plan(issue)
for _ in range(max_iters):
patch = edit(issue, p)
ok, report = test(patch)
history.append({"plan": p, "ok": ok})
if ok:
return patch, history
p = p + " | refine"
return patch, history
```
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Python",
"developer_needs": [
"repo_scale_reasoning",
"security_gates",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | e97ecdc6e8421085478f0324f9522b15a698fb93 | |
train_02185 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | compare | advanced | Task: compare
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "C#",
"developer_needs": [
"tests_are_truth",
"tooling",
"auditability",
"reproducibility"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | c52aaf9b1dc38c64eca808502da6cebdb23933a6 | |
train_02186 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | agent_loop | advanced | Task: agent_loop
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Go
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Loop: Plan → Edit → Test → Reflect → Human gate
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Go",
"developer_needs": [
"ci_integration",
"documentation",
"tests_are_truth",
"tooling"
],
"moe_experts": [
"evaluation_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | ccc1edc58bf4a70b3edf8e91f1dd493245d600ff | |
train_02187 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | design | intermediate | Task: design
Topic: Self-improving agents and feedback loops
Difficulty: intermediate
Target language: Python
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Python",
"developer_needs": [
"security_gates",
"ci_integration",
"repo_scale_reasoning",
"tooling"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5bbab08a6958b7b73fe9bc1090f6610b9d6b3b41 | |
train_02188 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | compare | intermediate | Task: compare
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: JavaScript
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"cost_latency_tradeoffs",
"documentation",
"security_gates",
"tests_are_truth"
],
"moe_experts": [
"coding_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 673dc9fd76b198dda9cb38a63037a4799f1aa89e | |
train_02189 | 2026-01-01T00:00:00 | Extended context and repo-scale understanding | review | expert | Task: review
Topic: Extended context and repo-scale understanding
Difficulty: expert
Target language: Java
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Java",
"developer_needs": [
"cost_latency_tradeoffs",
"tooling",
"ci_integration",
"governance"
],
"moe_experts": [
"agentic_systems_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | dc121c088a9fceeadf87af78c4ab3dca68bd0a40 | |
train_02190 | 2026-01-01T00:00:00 | Mixture-of-Experts (MoE) for code | failure_analysis | intermediate | Task: failure_analysis
Topic: Mixture-of-Experts (MoE) for code
Difficulty: intermediate
Target language: TypeScript
Context: Regulated environment requiring audit trails.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "TypeScript",
"developer_needs": [
"cost_latency_tradeoffs",
"reproducibility",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8f3b82c3b46ce5151983fdf71c7c46aa7b245ed4 | |
train_02191 | 2026-01-01T00:00:00 | Secure code generation and policy gates | review | expert | Task: review
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Review: correctness, security, performance, governance
| [] | {
"target_language": "Bash",
"developer_needs": [
"evaluation_metrics",
"repo_scale_reasoning",
"tooling",
"security_gates"
],
"moe_experts": [
"data_curation_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | fad3f353da4a91306839745f47bec11de1944f94 | |
train_02192 | 2026-01-01T00:00:00 | Model merging, distillation, and continued pretraining | failure_analysis | advanced | Task: failure_analysis
Topic: Model merging, distillation, and continued pretraining
Difficulty: advanced
Target language: TypeScript
Context: High-traffic service with latency SLOs.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "TypeScript",
"developer_needs": [
"tests_are_truth",
"auditability",
"reproducibility",
"repo_scale_reasoning"
],
"moe_experts": [
"agentic_systems_expert",
"security_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | b74a44bbbe0fe1c29a018d2eb343b04cecc7e94f | |
train_02193 | 2026-01-01T00:00:00 | Dataset curation pipelines (filter, dedupe, quality) | failure_analysis | expert | Task: failure_analysis
Topic: Dataset curation pipelines (filter, dedupe, quality)
Difficulty: expert
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"reproducibility",
"auditability",
"cost_latency_tradeoffs",
"documentation"
],
"moe_experts": [
"evaluation_expert",
"governance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 5d257b21a6ea355e1399874eba0c29fa0278de05 | |
train_02194 | 2026-01-01T00:00:00 | Secure code generation and policy gates | code | expert | Task: code
Topic: Secure code generation and policy gates
Difficulty: expert
Target language: SQL
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "SQL",
"developer_needs": [
"evaluation_metrics",
"governance",
"documentation",
"repo_scale_reasoning"
],
"moe_experts": [
"data_curation_expert",
"evaluation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 1238292f161b2b456f2e035de2c091ace498a261 | |
train_02195 | 2026-01-01T00:00:00 | Self-improving agents and feedback loops | failure_analysis | advanced | Task: failure_analysis
Topic: Self-improving agents and feedback loops
Difficulty: advanced
Target language: Java
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "Java",
"developer_needs": [
"documentation",
"security_gates",
"auditability",
"cost_latency_tradeoffs"
],
"moe_experts": [
"evaluation_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 3665d73eec4caa5f6bc548223a5d025346e396d3 | |
train_02196 | 2026-01-01T00:00:00 | SWE-bench style real-repo evaluation | code | advanced | Task: code
Topic: SWE-bench style real-repo evaluation
Difficulty: advanced
Target language: JavaScript
Context: Large monorepo with flaky tests and strict CI.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "JavaScript",
"developer_needs": [
"ci_integration",
"security_gates",
"tooling",
"cost_latency_tradeoffs"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 8becf246ccaec67b20ec2adc7d23475067c97900 | |
train_02197 | 2026-01-01T00:00:00 | Governance, provenance, and licensing for code data | compare | expert | Task: compare
Topic: Governance, provenance, and licensing for code data
Difficulty: expert
Target language: JavaScript
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Compare: capability, cost, latency, reliability
| [
"Identify failing behavior via tests",
"Minimize change surface",
"Apply patch",
"Run targeted + full suite",
"Verify no regressions"
] | {
"target_language": "JavaScript",
"developer_needs": [
"documentation",
"ci_integration",
"evaluation_metrics",
"tooling"
],
"moe_experts": [
"performance_expert",
"coding_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 61214afafc27331b46da9cbd0480fe9ec9e8d439 | |
train_02198 | 2026-01-01T00:00:00 | Multimodal dev workflows (docs, diagrams, traces) | explain | advanced | Task: explain
Topic: Multimodal dev workflows (docs, diagrams, traces)
Difficulty: advanced
Target language: Bash
Context: Research team validating claims against real repos.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Design with risks, metrics, acceptance criteria
| [] | {
"target_language": "Bash",
"developer_needs": [
"ci_integration",
"tooling",
"governance",
"reproducibility"
],
"moe_experts": [
"governance_expert",
"data_curation_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 0071a466c65c27287f837cd384f504d836564603 | |
train_02199 | 2026-01-01T00:00:00 | Latency, cost, and reliability optimization | failure_analysis | intermediate | Task: failure_analysis
Topic: Latency, cost, and reliability optimization
Difficulty: intermediate
Target language: C#
Context: Offline/local deployment with limited compute.
Produce expert-level, production-ready artifacts. | Facts:
- Modern AI coding prioritizes correctness, evaluation, and governance.
- Agentic loops with test gates outperform single-pass generation.
Failure:
- Initial patch broke edge case
Reflection:
- Missing zero-input guard
Correction:
- Add explicit validation + test
| [] | {
"target_language": "C#",
"developer_needs": [
"governance",
"auditability",
"tests_are_truth",
"repo_scale_reasoning"
],
"moe_experts": [
"coding_expert",
"performance_expert"
],
"governance": {
"audit_required": true,
"tests_required": true
}
} | 57c876e36c1db909a46df5de40acffd1c49c3895 |
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